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http://dx.doi.org/10.3795/KSME-A.2006.30.9.1116

Reliability Estimation Using Two-Staged Kriging Metamodel and Genetic Algorithm  

Cho, Tae-Min (한국과학기술원 기계공학과)
Ju, Byeong-Hyeon (한국과학기술원 기계공학과)
Jung, Do-Hyun (한국자동차부품연구원)
Lee, Byung-Chai (한국과학기술원 기계공학과)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.30, no.9, 2006 , pp. 1116-1123 More about this Journal
Abstract
In this study, the effective method for reliability estimation is proposed using tow-staged kriging metamodel and genetic algorithm. Kriging metamodel can be determined by appropriate sampling range and the number of sampling points. The first kriging metamodel is made based on the proposed sampling points. The advanced f'=rst order reliability method is applied to the first kriging metamodel to determine the reliability and most probable failure point(MPFP) approximately. Then, the second kriging metamodel is constructed using additional sampling points near the MPFP. These points are selected using genetic algorithm that have the maximum mean squared error. The Monte-Carlo simulation is applied to the second kriging metamodel to estimate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.
Keywords
Reliability; Kriging Metamodel; AFORM; Most Probable Failure Point; Genetic Algorithm;
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Times Cited By KSCI : 2  (Citation Analysis)
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